Grazing is often assumed to negatively impact the natural ecosystem and that removal of grazing would result in more pristine rangelands. However, rangelands provide many human benefits such as food production, income for rural families and communities, recreation, wildlife habitat, soil carbon sequestration, plant and animal biodiversity, and water filtration. Rangeland management practices influence the benefits received from these systems. The largest driver of forage and animal productivity, and economic return is proper stocking rate, and rotational or deferred grazing do not enhance these responses. But management intensive grazing practices allow forages to store reserves during times of abundant precipitation, increase water-holding capacity, provide wildlife habitat at critical times of rearing young, and create a shifting mosaic with both old and new growth vegetation all the while maintaining animal productivity and income for ranchers. Therefore, several management factors such as stocking rate, grazing management, and fire regime can impact the human benefits received from rangelands. The objective of this project was to determine the effect of stocking rate, grazing management and fire regime on indicators of environmental, social, and economic pillars of sustainability in different ecosystems across the Great Plains, and evaluate the collective sustainability of rangeland management scenarios.
Evaluation of rangeland management factors was accomplished using 3 simulation models: Agricultural Policy eXtender Model, Integrated Farm System Model, and economic input/output model (IMPLAN). Analysis focused on tallgrass, mixed, and shortgrass rangelands of the Great Plains region from eastern Kansas to eastern Montana capturing the Flint Hills, High Plains, and Sandhills regions. Six study sites were used and included the Konza Prairie Biological Station in Manhattan, KS, the Kansas State University Research and Education Center in Hays, KS, the High Plains Grasslands Research Station in Cheyenne, WY, the Gudmundsen Sandhills Laboratory in Whitman, NE, the Cottonwood Range and Livestock Field Station in Philip, SD and the Livestock and Range Research Laboratory in Miles City, MT. Twelve rangeland management scenarios were simulated from combinations of stocking rate (light, moderate, heavy), grazing management (continuous, rotational), and fire regime (no burn, spring burn). A no management scenario was also simulated where no grazing or fire were implemented. A meta-analysis of the effects of grazing on plant and animal biodiversity was completed with a focus on the North American Great Plains region approximately from Eastern Montana to Oklahoma encompassing the High Plains, Sandhills, Flint Hills, and Southern Plains. Animal groups of interest included birds, mammals, herptiles, and arthropods. Researchers categorized the effects of grazing on plant and animal groups into one of three categories based on reported results: positive, negative, and no effect. Researchers categorized stocking rates into three levels of grazing intensity (low, moderate, and high) based on geographic region. A summative model of net vitamin and mineral conversion was developed based on current industry diets and production parameters for the entire beef supply chain in the Southern Great Plains. Human-edible nutrient consumed in the beef supply chain was computed from ingredients used in typical beef cattle diets, and human-edible nutrient produced in the beef supply chain was computed from production of red meat and edible organs. Human-edible conversion ratio was then computed as the amount of human-edible nutrient produced in beef products to the amount of human-edible nutrient consumed in feed, thus a value greater than 1 indicates that the supply chain is a net contributor to the human diet. A sustainability index was computed by aggregating results from the 3 simulation models for soil health, climate, and economic metrics, as well as indicators of plant and animal biodiversity and net conversion ratios of human-edible nutrients. Each metric was weighted by an importance score assigned by 5 scientists and 2 producers, and normalized based on a sustainability limit value. A weighted average of all metrics was computed to create the index value.
The effect of rangeland management practices on soil health indicators, greenhouse gas emissions, and economics was highly dependent upon geographic location most likely due to differences in soil properties, forage species, and climatic conditions. One-size-fits-all prescription for the most sustainable management system will not produce the best results at all locations. Grazing at low and intermediate stocking densities had positive effects on plant and animal species throughout the North American Great Plains compared to areas that were not grazed. This is likely because grazing at these intensities created patterns in heterogeneous landscape composition and structure needed to enhance species diversity across a wide range of plant and animal groups. The beef supply chain is a net positive contributor of iron, phosphorus, vitamin B12, riboflavin, niacin, and choline to the human diet. The amount of corn grain consumed by cattle is a primary determinate of the net nutrient contribution of beef production systems. The rangeland management scenario with the greatest sustainability index value was not the same at all sites. The scenarios with the greatest index value had moderate to high index values for each of the 3 pillars (people, planet, profit), but did not necessarily have the greatest index value for any one pillar.
The results of this project stress the need for local evaluation of management practices by rangeland managers to develop the most sustainable management system for their environment. Implementing proper stocking rates and fire regimes can maintain or enhance plant and animal diversity. Enhancing the use of human-inedible byproducts in cattle diets will increase the net nutrient contribution of the beef industry. The most sustainable management system has positive indicators for all pillars but doesn’t necessarily maximize any one pillar.